Menu
Menu
Firms combining AI and IoT far more competitive than those using only IoT - study

Firms combining AI and IoT far more competitive than those using only IoT - study

“It is fair to say that most successful IoT operations are actually ‘AIoT’ operations,” says Oliver Schabenberger, chief operating officer at SAS.

Credit: Dreamstime

When two organisations using IoT compete with one another, the competitor using AI is more likely to achieve significant success

A new survey of global business leaders reveals the most significant predictor in getting value from Internet of Things (IoT) initiatives is the heavy use of artificial intelligence (AI). 

Ninety percent of survey respondents heavily using AI in their IoT operations reported exceeding value expectations, according to the study conducted by SAS, Deloitte and Intel with research firm IDC.

The respondents were 450 business leaders from around the world who were asked about their use of IoT and AI technologies.

The study showed organisations using IoT with AI appear to be more competitive than IoT-only enterprises by a double-digit margin across a variety of business indicators like employee productivity, innovation and operating costs.

Seen another way, when two organisations using IoT compete with one another, the competitor using AI is more likely to achieve significant success. 

“In these results, we’re seeing that organisations working with IoT data realise that if they want to get the real value out of it, they need AI and analytics,” says Oliver Schabenberger, chief operating officer at SAS.

“They’re using AI and analytics techniques to operate on their IoT data, as they should. I think it’s fair to say that most successful IoT operations are actually ‘AIoT’ operations.”

In the study, ‘AIoT’ refers to decision-making aided by AI technologies in conjunction with connected IoT sensor, system or product data. 

Credit: SAS

Organisations working with IoT data realise that if they want to get the real value out of it, they need AI and analytics

Oliver Schabenberger, SAS

AI technologies include deep learning, machine learning, natural language processing, voice recognition and image analysis.

The study finds companies that have developed AIoT capabilities report stronger results across critical organisational goals. These include the ability to speed up operations, introduce new digital services, improve employee productivity and decrease costs. 

For example, companies using IoT data to speed up operations without AI saw a 32 per cent increase. Companies adding AI to the mix saw speeds improve by 53 per cent.

AI opens the door to more sophisticated and rapid decision making that significantly affects results, the study points out.

“It broadens focus from operational problems like, ‘Is the equipment running or not?’ to decisions about supply and demand, product quality, retail merchandising, or the spread of illness in a healthcare facility.”

“AI and IoT are no longer in separate swim lanes,” observes Melvin Greer, chief data scientist at Intel Americas. 

“AI closes the loop in an IoT environment where IoT devices gather or create data, and AI helps automate important choices and actions based on that data,” says Greer.

“Today, most organisations using IoT are only at the first ‘visibility’ phase where they can start to see what’s going on through IoT assets. But they’re moving toward the reliability, efficiency and production phases, which are more sophisticated and require stronger AI capabilities.” 

Organisations must consider the ethical implications of combining AI and IoT

Schabenberger, meanwhile, says the key to driving long-term, sustainable value lies in an organisation’s ability to operationalise AIoT capabilities.

To operationalise, an organisation must push beyond isolated implementations and proofs of concept to deliver AIoT capabilities at scale throughout the organisation.

“The only way to increase the scale of AIoT throughout the organisation is to increase the level of automation,” says Schabenberger. 

“So many CIOs I talk with say automation is a primary focus, to make IoT-related analytics insights consumable by business analysts and others, not just the data scientists.”

The study, meanwhile, highlights an issue organisations need to consider as they combine the technologies.

“The ethical implications of AI are already being examined and challenged in a society becoming more attuned to the growing role that these technologies play in our lives today,” it states. “Model bias, privacy and security issues are only the starting points of this conversation.”

"If anything, combining AI with far-flung IoT capabilities only raises the stakes," it points out.

“Organisations that are already developing ethical standards to guide their technology usage in these areas must also be working to address the combination of AI and IoT.

“Those that are not yet considering the ethical implications should be actively planning to do so."  

Join the CIO New Zealand group on LinkedIn. The group is open to CIOs, IT Directors, COOs, CTOs and senior IT managers.

Join the newsletter!

Or

Sign up to gain exclusive access to email subscriptions, event invitations, competitions, giveaways, and much more.

Membership is free, and your security and privacy remain protected. View our privacy policy before signing up.

Error: Please check your email address.

Tags strategyprivacyCSRethicsintelbusiness intelligenceanalyticsIDCsasAItrustIoTethics of big dataOliver SchabenbergerAIoT

More about DeloitteIntelSAS

Show Comments